Abstract
Introduction:
The critically endangered hawksbill turtle (Eretmochelys imbricata) is essential for healthy coral reef ecosystems, and its gut microbiota plays a vital role in host nutrition and overall health. A comprehensive understanding of this microbial diversity is crucial for effective conservation, yet current knowledge remains limited. This study aimed to characterize the bacterial taxa present in the fecal samples of hawksbill turtles using culture-dependent methods.
Methods:
Fecal samples from hawksbill turtles were cultured under both aerobic and anaerobic conditions using two distinct bacterial media. A total of 161 bacterial strains were isolated and identified using standard microbiological techniques and 16S rRNA gene sequencing.
Results:
The isolated strains were classified into three phyla: Pseudomonadota (formerly Proteobacteria), Actinomycetota, and Bacillota (formerly Firmicutes). The most frequently identified species were Psychrobacter celer, Shewanella algae, Sulfitobacter pontiacus, Vibrio mytili, Enterococcus hirae, and Psychrobacter maritimus. Ten isolates were identified as potentially representing six novel bacterial species.
Discussion:
This study expands our understanding of the microbial diversity associated with hawksbill turtles. It demonstrates the utility of fast and simple culture-dependent approaches for characterizing the microbiota of endangered species, providing a foundation for future research into the roles of these bacteria in turtle health and reef ecosystem function.
1 Introduction
The hawksbill sea turtle (Eretmochelys imbricata) is classified as Critically Endangered on the International Union for Conservation of Nature Red List of Threatened Species due to intense commercial exploitation for its shell and meat, as well as the degradation of its nesting and marine habitats (). Although generally categorized as an omnivore, the hawksbill primarily feeds on sponges within coral reef ecosystems (). Unlike green sea turtles, which possess a cecum housing a rich microflora (), hawksbills lack this anatomical feature (). Emerging research highlights the mutualistic relationship between hosts and their resident microbiota, wherein hosts derive nutrients from microbial activity, and diet influences the gut microbiota composition and abundance (; Valdes et al., 2018). For instance, juvenile green turtles fast acquired polysaccharide fermenting gut microbiota after settlement into coastal habitats (). An investigation showed that the bacterial microbiota of sea turtles is heavily influenced by geography (). Additionally, a study indicated that despite the differences in origin, size and conditions of the animals, Firmicutes, Bacteroidetes, and Proteobacteria were dominant in the gut microbiome of all stranded sea turtles (). Similarly, gut microbiota enable hosts to ferment non-digestible substrates, fostering the growth of specialized microbial communities (Valdes et al., 2018). Lower bacterial diversity has been consistently observed in human diseases compared to healthy controls (; Wang et al., 2008; Turnbaugh et al., 2009; ; ; ; ), suggesting that gut microbiota diversity may serve as an indicator of host health (). These findings emphasize the critical roles of gut microbial communities in host nutrition and health. Consequently, a deeper understanding of gut microbiota diversity is vital for future conservation efforts targeting hawksbill turtles.
Although metagenomic approaches enable comprehensive sequencing of the entire metagenome, providing species-level assignments and genomic assemblies (Ye et al., 2019), microbial cultivation remains indispensable for elucidating microbial diversity and understanding their functional roles in hosts (; ; ). Notably, culture-dependent techniques can detect microorganisms present in low concentrations that may escape detection through metagenomic methods ().
In our previous study, high-throughput sequencing revealed that Bacteroidetes, Firmicutes, and Fusobacteria were the dominant gut microbial phyla in hawksbill sea turtles, reflecting the characteristics of both herbivorous and carnivorous sea turtles (). Additionally, enrichment analysis identified a high abundance of genes related to glycosyltransferases and auxiliary activities in the gut microbiota of hawksbill turtles (). However, these findings remain insufficient for a comprehensive understanding of gut microbiota diversity. Laboratory-based cultivation of gut bacteria offers a promising avenue for elucidating their roles in hawksbill turtles.
In this study, we used culture-dependent methods to characterize the bacterial taxa isolated from hawksbill fecal samples, with the aim of providing a more detailed understanding of gut microbiota diversity in this critically endangered species.
2 Materials and methods
2.1 Animals and sampling
This study was approved by the Committee on Biomedical Ethics of Huizhou University. We collected 14 fecal samples from hawksbill turtles (Eretmochelys imbricata) residing in the Sea Turtles National Nature Reserve, Huidong, China (22°33′15′′N; 114°52′33′′E). A total of 14 hawksbills inhabit the reserve. The healthy hawksbills were hosted in tanks, and were fed mainly small sea fish with a small amount of vegetables. The ages of the first and second batches of hawksbill turtles were 7, 12 years, respectively. Each batch included five females and two males. Fecal samples were collected from each turtle near their feeding time (stools produced after feeding), which made sampling difficult. Therefore, we decided to collect fecal samples in two batches. Seven samples were collected on August 4, 2022 (first batch), and the remaining seven were collected on August 9, 2022 (second batch). All sampling tools were sterilized at high temperature (121°C) and high pressure (105 kPa) for 30 min before being oven-dried. To minimize contamination from the surrounding water, the fecal pellet cores were accessed using sterilized forceps and sampled with sterile swabs. Buffers were not used during collection. After sampling, fecal samples were immediately placed in cryogenic vials, flash-frozen in liquid nitrogen, transported to the laboratory, and stored at −80°C until further processing.
2.2 Culture-dependent identification of bacteria in hawksbill feces
The culture-dependent isolation of bacterial samples from hawksbill feces was conducted following the method described by , with minor modifications. Strict sterile procedures were followed throughout the process. Both anaerobic and aerobic conditions were used to obtain a greater variety of microorganisms. Under aerobic conditions: 1) Two grams of each fecal sample were homogenized in 20 mL of sterile seawater using a sterilized motorized pellet pestle until the samples were thoroughly broken down into small particles. 2) A 100-µL aliquot of the homogenized solution was serially diluted up to a 10-9 dilution in sterile seawater. Aliquots from dilutions of 10-7, 10-8, and 10-9 were plated onto two types of agar-based solid media: 2216E supplemented with 1 g/L sodium acetate (M1) and 2216E supplemented with 25 g/L jellyfish extract (M2) (2216E; Table 1), and then incubated at 28°C. 1) and 2) were performed on a laminar flow bench to avoid contamination. Anaerobic conditions: 1) were the same as aerobic conditions; and 2) aliquots from dilutions of 10-7, 10-8, and 10-9 were plated onto M1 agar-based solid media, placed in an anaerobic bag, and incubated at 28°C. Here, 1) and 2) were performed on Baker Ruskinn Consept 400.
Table 1
| Chemical composition | Content (g/L) |
|---|---|
| Protein peptone | 5.0 |
| Yeast powder | 1.0 |
| Iron citrate | 0.1 |
| Sodium chloride | 19.45 |
| Magnesium chloride | 5.98 |
| Sodium sulphate | 3.24 |
| Calcium chloride | 1.8 |
| Potassium chloride | 0.55 |
| Sodium carbonate | 0.16 |
| Potassium bromide | 0.08 |
| Strontium chloride | 0.034 |
| Boric acid | 0.022 |
| Sodium silicate | 0.004 |
| Sodium fluoride | 0.0024 |
| Ammonium nitrate | 0.0016 |
| Disodium hydrogen phosphate | 0.008 |
| Total | 37.4284 |
Composition of the 2216E medium used to cultivate marine bacteria.
Footnote: Briefly, 37.4284 g of this product was completely dissolved in 1000 mL of distilled water by stirring slowly at 25°C. Subsequently, the solution was sterilized for 15 min at 121°C. After sterilization, it should be shaken thoroughly to allow the sediment to disperse as much as possible to avoid aggregation and affect the experiment.
The plates were monitored daily for bacterial colony growth. Multiple diluted plates of the same sample were used for colony comparison, and different strains were selected. A purified single colony was obtained by repeated streaking on a plate. A certain amount of a single colony was then added to TE buffer from the purified plate for subsequent DNA extraction.
2.3 16S rDNA-based taxonomic characterization of bacterial clones
DNA was extracted from bacterial cells using the Silicone Bacterial Genomic DNA Extraction Kit (Shanghai SBS Genetechnology Co., Ltd.). The extracted DNA was amplified by polymerase chain reaction (PCR) using the primers described by : 27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-ACGGCTACCTTGTTACGACT-3′). Each 50 µL PCR reaction contained 1 µL DNA template (> 20 ng), 0.2 µL Taq polymerase, 5 µL 10× reaction buffer, 4 µL 2.5 mM dNTPs, 1 µL each of 10 µM forward and reverse primers, 4 µL of 25 mM MgCl2, and 20.7 µL dH2O. The thermal cycling conditions were as follows: initial denaturation at 94°C for 1 min; 30 cycles of denaturation at 94°C for 1 min, annealing at 55°C for 1 min, and extension at 72°C for 1.5 min; final elongation at 72°C for 10 min; and hold at 10°C. The PCR products were sequenced using the Illumina NovaSeq 6000 system (Novogene, Beijing, China). The EzTaxon database contains sequences of type strains of prokaryotic species with validly published names. Type strains serve as the nomenclatural types for bacterial and archaeal species in taxonomy. They are used as reference points for identifying and classifying new isolates. Therefore, the 16S rRNA gene sequence data were compared and analyzed using the EzTaxon bacterial type species database (http://www.ezbiocloud.net/eztaxon/ify) to construct a phylogenetic tree. A comparison was also made at the NCBI database (http://blast.ncbi.nl.nih.gov/Blast.cgi) to check whether there were other type species that had not been included in EzTaxon. Following , species identification was conducted using a combination of 16S rRNA sequence similarity and DNA–DNA hybridization (DDH) similarity. First, a 16S-based search (Yoon et al., 2017) identified candidate species for comparison to the strain of interest. Only species with ≥ 98.7% 16S similarity were selected (). DDH techniques are the gold standard for the genomic similarity analyses of pairwise strain sets for classification. Subsequently, DDH similarity was assessed, with ≥ 70% similarity used as the threshold for species boundaries (). If DDH similarity was < 70%, the isolate was considered a potential new species, even if the 16S similarity was ≥ 98.7%. New species candidates were further analyzed through complete genome sequencing.
2.4 Complete genome sequencing of potential new species
Genomic DNA was extracted from bacterial strains identified as potential new species using the OMEGA Bacterial Genomic DNA Extraction Kit. DNA was quantified using a TBS-380 fluorometer (Turner BioSystems Inc., Sunnyvale, CA). High-quality DNA samples (OD260/280 = 1.8–2.0, > 6 µg) were used to construct DNA libraries. Genomic DNA (1 µg) was fragmented into 300–500 bp segments using a Covaris M220 ultrasonicator. The fragmented DNA was end-repaired, adenylated at the 3′ ends, and ligated with indexed adapters using the TruSeq™ Nano DNA Sample Prep Kit. The resulting DNA library was enriched by PCR amplification for eight cycles. Target bands were recovered using 5.2% Certified Low Range Ultra Agarose gel electrophoresis and quantified using the TBS-380 fluorometer (Picogreen). The enriched libraries were proportionally pooled for sequencing. Bridge PCR amplification was performed on a cBot solid-phase carrier to generate clusters, and the libraries were sequenced using the Cyclone SEQ platform (www.biozeron.com).
2.5 Data analysis and genome assembly
The original image data were converted into sequence data using Base Calling, with results stored in the FASTQ file format. The raw data were filtered using the Trimmomatic tool (ILLUMINACLIP:adapters.fa:2:30:10 SLIDINGWINDOW:4:15 MINLEN:75) (http://www.usadellab.org/cms/index.php?page=trimmomatic) to improve the accuracy of the subsequent assembly. The filtering process involved several steps: 1) removing adapter sequences from the reads and trimming non-AGCT bases at the 5′ end; 2) trimming the ends of reads with low sequencing quality (Q-value < Q20); 3) eliminating reads containing more than 10% ambiguous bases (N); and 4) discarding small fragments < 75 bp after adapter removal and quality trimming. The resulting clean reads were assembled de novo using ABySS v2.0.2 (http://www.bcgsc.ca/platform/bioinfo/software/abyss) with optimized K-mer parameters to generate the best possible assembly sequences. Further assembly refinement included filling gaps and correcting base errors using GapCloser v1.12 (https://sourceforge.net/projects/soapdenovo2/files/GapCloser/). Clean reads were aligned with the assembled genome sequences to calculate the GC content and coverage depth. The reliability and normality of the assembly results were assessed by determining the overall GC content distribution and coverage depth.
2.6 Gene annotation and phylogenetic tree construction
The predicted protein sequences of genes were aligned against the NR, KEGG, eggNOG, STRING, and GO databases using BLAST+2.7.1 with an alignment threshold of E-value ≤ 1e-5. This process provided a comprehensive annotation of the predicted genes. OrthoMCL v2.0.3 was used to align the amino acid (or nucleotide) sequences of all the analyzed species to identify homologous genes. Similarity clustering was performed with the parameters BLASTP E-value ≤ 1e-5 and MCL_INFLATION=1.5, yielding a list of homologous gene clusters. Phylogenetic analysis was based on GTDB-Tk and FastTree (). Using ​GTDB-Tk v2.4.0 (database release ​R220), we extracted and aligned sequences of ​120 bacterial marker genes from the target genomes. A ​maximum-likelihood tree was constructed using ​FastTree 2.1.11 with default parameters. Owing to resolution limitations in the figure, the bootstrap support values are not clearly visible; however, the corresponding Newick-format tree file is provided as Supplementary Data.
3 Results
3.1 Bacterial taxa from hawksbill feces cultured on M1 medium under aerobic conditions
Bacterial isolates from the first batch of samples cultured on M1 medium under aerobic conditions were subjected to 16S rRNA gene sequencing. Sequence alignment identified 77 bacterial isolates, which were assigned to 39 distinct species. At the phylum level, 46 isolates were classified as Pseudomonadota, 10 as Bacteroidota, 13 as Actinomycetota, and eight as Bacillota. The isolates were predominantly classified at the genus level as Psychrobacter, Tenacibaculum, Glutamicibacter, Shewanella, Vibrio, and Pseudoalteromonas. The most frequently isolated species included Psychrobacter celer, Shewanella algae, Tenacibaculum discolor, Tenacibaculum mesophilum, Pseudoalteromonas tetraodonis, Vibrio neocaledonicus, Alcaligenes faecalis subsp. phenolicus, and Rheinheimera aquimaris, with Psychrobacter celer being the most common isolate (Figure 1).
Figure 1
Among the 77 isolates, six displayed ≥ 98.7% 16S rRNA gene sequence similarity with known species, including Glutamicibacter arilaitensis (98.79%), Mesonia sediminis (98.25%), Rhodococcus phenolicus (98.92%), and Alcanivorax borkumensis (98.94%). However, DDH analysis revealed a similarity of < 70% for these six isolates, suggesting that they may represent novel species. These isolates were subsequently selected for complete genomic sequencing. The 16S rRNA genes of bacterial isolates from the second batch of samples were amplified and sequenced under aerobic conditions. Sequence alignment identified 31 isolates, which were assigned to 17 distinct species. At the phylum level, 23 isolates belonged to Pseudomonadota, five to Bacillota, two to Bacteroidota, and one to Campylobacterota. The isolates were primarily assigned to Sulfitobacter, Psychrobacter, Sporosarcina, and Pseudoalteromonas at the genus level. The most frequently isolated species included Sulfitobacter pontiacus, Sporosarcina aquimarina, Pseudoalteromonas carrageenovora, Psychrobacter piscatorii, and Psychrobacter cibarius, with Sulfitobacter pontiacus being the most common isolate (Figure 2).
Figure 2
A comparison of isolates from the first and second batches revealed a dominance of isolates from the phyla Pseudomonadota, Actinomycetota, and Bacillota in both batches. Differences were primarily observed at the genus and species levels, reflecting variations in microbial composition based on sampling time. Overall, these results demonstrated an unexpectedly high diversity of bacterial taxa identified using the culture-dependent approach.
3.2 Bacterial taxa cultured from hawksbill feces on M1 under anaerobic conditions
A total of 38 bacterial strains, representing 18 species, were isolated from the first batch of samples under anaerobic cultivation conditions. At the phylum level, 24 isolates belonged to Pseudomonadota, 11 to Bacillota, and three to Bacteroidota. The isolates were primarily assigned to Shewanella, Vibrio, Enterococcus, and Frondibacter at the genus level. Among these, the most frequently identified species were Shewanella algae, Vibrio mytili, Enterococcus hirae, Frondibacter mangrovi, and Paraclostridium benzoelyticum, with Shewanella algae being the most prevalent isolate (Figure 3). Seven species were found under both anaerobic and aerobic conditions on M1 media: Psychrobacter celer, Shewanella algae, Alcaligenes faecalis subsp. phenolicus, Enterococcus hirae, Vibrio plantisponsor, Psychrobacter alimentarius, and Vibrio mytili. A comparison of the microorganisms isolated under anaerobic and aerobic conditions revealed both similarities and differences. In both conditions, most isolates belonged to the phylum Pseudomonadota. However, notable differences were observed at the genus and species levels, highlighting the impact of cultivation conditions on the diversity of isolates.
Figure 3
3.3 Bacterial taxa cultured from hawksbill feces on M2 under aerobic conditions
The 16S rRNA genes of bacterial isolates grown on aerobic M2 medium were amplified and sequenced. Sequence alignment revealed that 15 bacterial strains were isolated, representing 9 distinct species. At the phylum level, eight isolates belonged to Pseudomonadota, four to Bacteroidota, two to Bacillota, and one to Actinomycetota. At the genus level, the isolates were primarily assigned to Psychrobacter and Frondibacter. Among the 15 isolates, the most frequently identified species was Psychrobacter maritimus, which accounted for five isolates (33.33%). The second most common species was Frondibacter mangrovi (Figure 4). Notably, four isolates showed 16S rRNA gene similarity to Frondibacter mangrovi (94.63%) and Glutamicibacter halophytocola (98.99%), but DDH similarity was < 70%, indicating that these isolates represent potentially novel species. These isolates were selected for further analysis, including complete genomic sequencing. A comparison of bacterial isolates based on the medium composition (M1 versus M2) revealed both similarities and differences. At the phylum level, Pseudomonadota was the most commonly identified group in isolates from both media. However, the addition of jellyfish extract to M2 resulted in a significant reduction in the number of isolates compared to M1 under aerobic conditions. Differences were also observed at the genus and species levels.
Figure 4
3.4 Phylogenetic analysis and gene enrichment for potential new species
Phylogenetic analysis revealed that six potential new species isolated from hawksbill feces were grouped into five distinct clusters (Figure 5). Among them, four species (designated as DM7, DM50, DM51, and DM55) were isolated from hawksbill feces on M1 medium under aerobic conditions, whereas two species (DS3 and DS5) were isolated from hawksbill feces on M2 medium under aerobic conditions. Interestingly, isolates from different media did not exhibit a distinct phylogenetic distribution. For instance, both DM7 and DS3 belonged to the genus Glutamicibacter. DM50, DM51, and DM55 were classified under the genera Mesonia, Rhodococcus, and Alcanivorax, respectively. Notably, DS5 was assigned to the genus Enterococcus_B, which differed from its initial classification based on 16S similarity. Further functional analyses were conducted using the whole genomic sequences of these potential new species, with gene functions annotated through KEGG pathway analysis. Genes from DS3 and DS5 showed partial similarity, both being enriched in carbohydrate metabolism pathways, although they also exhibited functional differences (Supplementary Figures 1, 2). Similarly, genes from DM7, DM50, DM51, and DM55 shared some common features, particularly their enrichment in amino acid metabolism pathways, while also displaying unique functional characteristics (Supplementary Figures 3-6). Notably, the gene functions of DS3 and DM7 exhibited a high degree of similarity, with both being enriched in pathways related to amino acid metabolism, carbohydrate metabolism, membrane transport, nucleotide metabolism, and translation. This observation suggests that species within the same genus may share highly similar functional profiles.
Figure 5
4 Discussion
The animal gut microbiota, primarily composed of bacteria, plays a crucial role in influencing the host’s fitness, phenotype, and health by performing various functions traditionally attributed to the host itself (; ). However, the sheer abundance and diversity of bacteria in the gut pose significant challenges for researchers attempting to identify their taxa. Although metagenomic methods enable the sequencing of entire metagenomes, offering species-level assignments and complete genomic assemblies (), culture-dependent approaches seem redundant. Nonetheless, culture-dependent techniques remain invaluable for detecting microorganisms present in low concentrations that may be undetected by metagenomics. In this study, we observed significant differences in bacterial taxa identified via culture-dependent techniques compared to those identified using metagenomic methods. Our previous metagenomic studies revealed that the gut bacteria of hawksbills primarily belong to the phyla Bacteroidetes, Firmicutes, and Fusobacteria (). In contrast, the majority of bacterial isolates obtained through culture-dependent methods belonged to the phyla Pseudomonadota (formerly Proteobacteria), Actinomycetota, and Bacillota (formerly Firmicutes). Pseudomonadota is among the predominant phyla in natural environments, including marine ecosystems (; ; ), and on the carapace of hawksbill turtles (), yet remains relatively underexplored compared to other groups (Zhang et al., 2018; ). Similarly, Actinomycetota, which are widely distributed across diverse ecosystems such as soil, freshwater, and marine environments (Stach and Bull, 2005; ), are recognized as a valuable source of antibiotics (). Bacillota, another major phylum, is strongly associated with marine organisms and is ubiquitous in terrestrial and aquatic environments (Viju et al., 2021). At the genus level, metagenomic analyses from our previous studies identified Cetobacterium, Bacteroides, and Paludibacter as the most abundant genera in hawksbill gut microbiota (). In contrast, Psychrobacter emerged as the dominant genus in our culture-dependent results, followed by Glutamicibacter and Vibrio. These discrepancies between the two approaches underscore the complementary nature of metagenomic and culture-dependent techniques.
In this study, more isolates were obtained from M1 medium under aerobic conditions than under anaerobic conditions. Under aerobic conditions, the strains isolated from M1 medium predominantly belonged to three species: Psychrobacter celer, Sulfitobacter pontiacus, and Shewanella algae. Psychrobacter celer is of particular interest because of its psychrophilic or psychrotolerant characteristics, which make it a promising candidate for industrial applications (). Therefore, hawksbill fecal samples could serve as a valuable resource for isolating Psychrobacter celer. Another species, Sulfitobacter pontiacus, previously isolated from the Black Sea, is well known for producing a highly active, soluble AMP-independent sulfite oxidase. This enzyme has significant potential for use in biosensor systems to detect sulfite in food and beverages (). Thus, the isolation of Sulfitobacter pontiacus from hawksbill fecal samples represents a practical approach for accessing this biotechnologically valuable species. Under anaerobic conditions, Shewanella algae was the most frequently isolated species. Shewanella spp. are known for their ability to thrive in remarkably diverse environmental conditions (; Yang et al., 2007; ; ; ). However, it is important to note that Shewanella algae is increasingly recognized as a conditionally pathogenic bacterium, capable of causing infections in humans and aquatic animals (; ). This highlights the need for caution when studying its presence in hawksbill turtles. Vibrio mytili was another notable species isolated from the M1 medium under aerobic conditions. Various studies have reported Vibrio spp. infections in fish worldwide (). Additionally, Vibrio mytili has demonstrated high resistance to erythromycin in groupers (). Further investigation is necessary to assess the potential impact of this bacterium on the health of hawksbill turtles.
The top-hit species isolated from strains cultured on M2 medium included Psychrobacter maritimus, along with other notable species such as Pseudomonas caeni, Carnobacterium jeotgali, Enterococcus hirae, Halomonas venusta, Winogradskyella crassostreae, and Shewanella algae. The addition of jellyfish to the medium appeared to significantly reduce the number of isolates, potentially due to the effects of their venom (). Psychrobacter maritimus, originally isolated from coastal sea-ice and sediment samples (), is a psychrophilic Bacillus. This genus has been proposed as a potential probiotic to enhance feed utilization, digestive enzyme activity, and innate immunity in groupers (Yang et al., 2011). Future research should explore the effects of Psychrobacter maritimus on hawksbill turtle health. Notably, Pseudomonas caeni is a carbapenem- and tigecycline-resistant bacterium that was previously isolated from chicken feces (). Carnobacterium jeotgali, initially identified in Korean traditional fermented food (), has also been detected in the rumen microbiota (). Enterococcus hirae, the first reported anticancer probiotic (Viaud et al., 2013), has more recently emerged as one of the most common opportunistic pathogenic bacteria in poultry (). Halomonas venusta is a moderately halophilic marine bacterium (), whereas Winogradskyella species are widely associated with marine organisms (; ). Winogradskyella has also been linked to amebic-induced fish gill diseases (, ). However, the specific role of Winogradskyella crassostreae in hawksbill turtles remains unclear. Further investigations are needed to determine its potential effects on the health of hawksbill turtles.
Further, based on 16S rRNA gene sequencing, we found a notable difference in species diversity between the first and second batches of bacterial isolates cultured on M1 medium under aerobic conditions. The ages of the first and second batches of hawksbill turtles were different, which may lead to differences in the diversity of isolated species. Indeed, reported that cloacal bacterial diversity and structure changes with age in loggerhead sea turtles.
Similarity analysis based on 16S rRNA gene sequencing and DDH indicated that ten isolated strains were likely novel species. Subsequently, these strains were selected for complete genome sequencing. Phylogenetic analysis revealed that the ten isolates belonged to five distinct genera. Gene enrichment analysis further suggested that species within the same genus exhibited highly similar functional profiles. In summary, culture-dependent techniques are essential and a valuable complement to metagenomic approaches. Finally, our study had some limitations. First, our samples did not allow us to identify the gut bacteria of wild hawksbill turtles (Eretmochelys imbricata) because all samples were collected from the hawksbill turtles (Eretmochelys imbricata) in a nature reserve. Further studies are needed to comparatively analyze the fecal bacteria of captive and wild hawksbill turtles (Eretmochelys imbricata) to identify and differentiate between the original and introduced bacteria.
5 Conclusion
In this study, we employed culture-dependent techniques to detect bacterial taxa that may be overlooked using metagenomic methods. A total of 161 bacterial strains were successfully isolated using two types of media under aerobic and anaerobic conditions. The most frequently identified species included Psychrobacter celer, Shewanella algae, Sulfitobacter pontiacus, Vibrio mytili, Enterococcus hirae, and Psychrobacter maritimus. In addition, six new species were identified based on 16S rRNA gene sequence similarity and DDH analysis. These findings suggest that culture-dependent methods may be a valuable complement to metagenomic approaches for the detection and identification of bacterial isolates.
Statements
Data availability statement
The original sequence data for the six new species are available at the SRA under the accession number PRJNA1262675 (https://www.ncbi.nlm.nih.gov/sra/PRJNA1262675).
Ethics statement
The animal studies were approved by the Committee on Biomedical Ethics of Huizhou University. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent was obtained from the owners for the participation of their animals in this study.
Author contributions
HL: Supervision, Methodology, Conceptualization, Validation, Investigation, Writing – review & editing, Formal Analysis, Writing – original draft, Project administration, Funding acquisition. YC: Investigation, Funding acquisition, Writing – review & editing, Conceptualization, Formal Analysis, Data curation, Methodology. ZX: Writing – review & editing, Investigation, Conceptualization, Resources, Visualization. YL: Investigation, Writing – review & editing, Resources, Validation, Formal Analysis, Conceptualization, Methodology. RX: Visualization, Resources, Investigation, Conceptualization, Writing – review & editing, Software, Methodology, Formal Analysis.
Funding
The author(s) declare financial support was received for the research and/or publication of this article. This study was supported by the Educational Commission of Guangdong Province, China (Grant No. 2020ZDZX1050) and the Science and Technology Planning Project of Huizhou City, China (Grant No. 2020SC0302019).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declare that no Generative AI was used in the creation of this manuscript.
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2025.1671894/full#supplementary-material
Supplementary Figure 1KEGG enrichment analysis of genes from DS3.
Supplementary Figure 2KEGG enrichment analysis of genes from DS5.
Supplementary Figure 3KEGG enrichment analysis of genes from DM7.
Supplementary Figure 4KEGG enrichment analysis of genes from DM50.
Supplementary Figure 5KEGG enrichment analysis of genes from DM51.
Supplementary Figure 6KEGG enrichment analysis of genes from DM55.
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Summary
Keywords
culture-dependent methods, 16S rRNA gene similarity, DDH similarity, bacterial isolates, gut microbiota
Citation
Li H, Chen Y, Xia Z, Lin Y and Xu R (2025) Analysis of the gut-specific microbiome from critically endangered hawksbill sea turtles (Eretmochelys imbricata) using a culture-dependent approach. Front. Mar. Sci. 12:1671894. doi: 10.3389/fmars.2025.1671894
Received
23 July 2025
Accepted
15 September 2025
Published
03 October 2025
Volume
12 - 2025
Edited by
Vikash Kumar, Central Inland Fisheries Research Institute (ICAR), India
Reviewed by
Javad Loghmannia, Shahid Beheshti University, Iran; Biswajit Mandal, Central Inland Fisheries Research Institute (ICAR), India
Updates
Copyright
© 2025 Li, Chen, Xia, Lin and Xu.
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*Correspondence: Hongwei Li, lhwcau@163.com
These authors share first authorship
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